I construct a new proxy for Tobin’s Q that incorporates the replacement cost of patent capital. This proxy, which I call patent Q , explains up to 62% more variation in investment than other proxies for Q. Furthermore, investment is more sensitive to patent Q than to other proxies for Q. Although investment is predicted more accurately by, and is more sensitive to, patent Q , controlling for patent Q leads to relatively larger, not smaller, cash flow coefficients. All results are stronger in subsamples with more patent capital. Overall, patent Q strengthens the historically weak investment– Q relation.

We document a strong, negative relation between the curvature of stock price paths (i.e., price-path convexity) and future short-horizon returns at both the aggregate and firm levels. This relation obtains regardless of the cumulative return during the convexity estimation period. At the aggregate level, convexity is a better predictor of future returns than many commonly used predictors. At the firm level, this effect is not explained by known return predictors, microstructure frictions, or illiquidity. Using survey-based expectations of short-horizon returns, we show that the negative relation between convexity and future returns is driven in part by overextrapolation of past returns.

We show that small innovators (i.e., small firms with recent patent grants) earn higher future returns than small non-innovators. However, we find no such innovation premium among large firms. The higher returns are driven by risk, not underreaction to announcements of recent patent grants. We find that being small and innovative interacts with financial constraints to explain the higher returns. These interactions are more important in the presence of greater information asymmetry. The higher cost of equity among small innovators has implications for their investment, growth, and capital structure decisions.